Find a Data Champion

Aurora is a PhD student at the University of Cambridge. Prior to earning her MPhil degree from Cambridge with Distinction and Best Dissertation Award, she majored in Spanish and minored in Psychology with a First and Best Dissertation Award. Her research lies at the intersection of applied linguistics, psychology, and sociology. In addition to research training in areas such as experimental design, she is particularly interested in digital scholarship and open research.

Can Jin completed her PhD in Education at the University of Cambridge and is currently a researcher at Cambridge University Press & Assessment. In this role, she supports good research practice, designs and manages research projects, conducts appropriate data analyses, and disseminates findings through reports, research papers, and presentations.

In my role as Academic Services Librarian, I manage services delivered in the Haddon Library with a specific focus on supporting teaching and research for the Departments of Archaeology and Social Anthropology. I am also the Research Support Lead for the Humanities and Social Sciences Libraries Team, working across the School of HSS to support research excellence and training as well as assisting in exercises such as the REF.

Additional areas of expertise: Information literacy, Research communication, Public engagement, Creative Commons, Open sharing.

As the Research Support Librarian at the Department of Engineering I am part of the Technology Libraries team providing library services for the Departments of Engineering, Chemical Engineering and Biotechnology, and Computer Science and Technology. My role includes providing training and advice on research data management and open data. I became a Data Champion in my previous role as the Library Manager at the Cambridge Conservation Initiative, supporting nature conservation researchers from the university and NGOs. I have previous experience, from research during masters degrees, working with ethnographic data in libraries and statistical analysis of palaeobiology data using R.